Microstructural changes precede depression in patients with relapsing-remitting Multiple Sclerosis

Background Multiple Sclerosis lesions in the brain and spinal cord can lead to different symptoms, including cognitive and mood changes. In this study we explore the temporal relationship between early microstructural changes in subcortical volumes and cognitive and emotional function in a longitudinal cohort study of patients with relapsing-remitting Multiple Sclerosis. Methods In vivo imaging in forty-six patients with relapsing-remitting Multiple Sclerosis was performed annually over 3 years magnetic resonance imaging. Microstructural changes were estimated in subcortical structures using the free water fraction, a diffusion-based MRI metric. In parallel, patients were assessed with the Hospital Anxiety and Depression Scale amongst other tests. Predictive structural equation modeling was set up to further explore the relationship between imaging and the assessment scores. In a general linear model analysis, the cohort was split into patients with higher and lower depression scores. Results Nearly all subcortical diffusion microstructure estimates at the baseline visit correlate with the depression score at the 2 years follow-up. The predictive nature of baseline free water estimates and depression subscores after 2 years are confirmed in the predictive structural equation modeling analysis with the thalamus showing the greatest effect size. The general linear model analysis shows patterns of MRI free water differences in the thalamus and amygdala/hippocampus area between participants with high and low depression score. Conclusions Our data suggests a relationship between higher levels of free-water in the subcortical structures in an early stage of Multiple Sclerosis and depression symptoms at a later stage of the disease.

M ultiple Sclerosis (MS) is an inflammatory and degenerative central nervous system disease characterized by demyelination, axonal loss and gliosis 1 . Clinically, the disease is typically associated with impairment of motor and sensory function, but also cognitive and emotional functions that commonly lead to progressive disability with reduced quality of life and shortened life expectancy. The diagnosis is based on the history of symptoms, clinical findings, and measures derived from MRI examinations and cerebrospinal fluid (CSF) analyses 2 . Most patients (85-90%) experience a relapsing-remitting disease course (RRMS), and 10-15% experience a primary progressive (PPMS) or secondary progressive (SPMS) course. A hallmark of RRMS is high disease activity in terms of lesions with distinct attacks and remission periods, while PPMS and SPMS have fewer lesions and are marked by a gradual worsening of symptoms without any distinct attacks or remission periods 1 . New disease activity is most often visible as lesions on MRI images, and brain changes are expected to be present before the core clinical symptoms of the disease. In the present longitudinal study, we investigate associations between the brain measures and clinical symptoms in a group of recently diagnosed patients with RRMS.
Longitudinal recording of clinical relapses, disability progression evaluated by the Expanded Disability Status Scale (EDSS) 3 , as well as the identification of new lesions on structural MRI images 2 are key elements when identifying and monitoring patients with MS. In addition to identifying lesions, MRI research has been employed to better understand the pathophysiology of the disease. Popular areas of MRI research aim to provide complimentary measures of inflammation 4 , brain atrophy through volumetry 5 and using functional MRI (fMRI) experiments to observe changes in functional connectivity 6 and brain activation 7 . In addition, non-invasive diffusion MRI has been used to quantify changes in white matter structures 8 by using mathematical modeling to infer both micro and macroscopical changes in tissue based on probing the free random movement of water molecules 9,10 . Abnormalities in diffusion MRI, such as reduced fractional anisotropy (FA), have been shown to be a marker of diffuse demyelination 11 and to be associated with cognitive impairment in patients with MS 12 . As MS is considered to primarily be a brain white matter disease, the focus of diffusion MRI research studies has predominantly targeted structural changes within the white matter 13,14 .
The free water fraction (FWF) is another diffusion-based method that aims to disentangle the free water contribution from the diffusion signal 15 . It has previously been used to estimate the fraction of extracellular water in applications such as quantifying the contribution of edema in tumors and the tissue surrounding lesions in MS [16][17][18][19][20] . The FWF can also be estimated from other diffusion models 21 . Fluid accumulation, akin to edema is one of the hallmarks of inflammation and is generally regarded as a firstorder immune response 22 . It has been suggested that inflammation and depression may be linked 23 , thus, a imaging metric to estimate free water may provide a surrogate biomarker to assess inflammation in vivo.
Depression, anxiety, and fatigue are common among patients with MS, with symptoms that significantly impair patients' quality of life [24][25][26][27][28] . This occurs despite progress in treatments currently available for the disease.
Although living with a disabling disease with increasing loss in motor function, among other life-limiting symptoms, definitely can lead to depression, a more direct impact of subcortical microglial activation, lesion burden, and regional atrophy has also been suggested 24,26,27 .
A recent study found that MS patients are more likely to develop clinical depression during pregnancy 29 . Volumetric abnormalities in the basal ganglia has for example recently been demonstrated to be a predictor of fatigue in a large cohort of MS patients 30 . Moreover, the basal ganglia has also been suggested to play a role in depression 31 in general. In studies including diffusion MRI, abnormalities in subcortical gray matter have also previously been observed in MS [32][33][34][35][36] . The subcortical structures including the basal ganglia are therefore particular targets of investigations in this current study.
Similarly, cognitive function is also shown to be affected in patients with MS, at any stage and subtype of the disease [37][38][39][40][41] . The prevalence and severity of cognitive impairment appears greatest in PPMS and SPMS 42 . It has recently been shown in studies including the Brief International Cognitive Assessment for MS (BICAMS) tests 43 , that the results on psychometric tests of processing speed as well as verbal and visual memory were correlated with whole brain and gray matter volume measures derived from an MRI examination at baseline 44 . After 2 years, the authors found significant changes in these global volumes that allowed differentiation of patients that were defined as either cognitively impaired or preserved.
Generally, the prevalence of cognitive impairment in MS ranges from 34 to 65% and depression is a symptom in one of four patients between the ages of 18-45 26,45 . Zabad et al. found that patients suffering from PPMS were less at risk to suffer from major depression than RRMS patients 46 .
From the studies referred to above, we expect to find associations between MRI-derived measures of subcortical structures and results on cognitive tests and scales assessing fatigue and depression in patients with relapsing-remitting MS. In this study, brain measures are derived from different MRI modalities. Considering the strict interplay described between depression and parenchymal structural changes, a focus will be given to the question whether pathological changes detected by diffusion MRI in the subcortical structures can predict worsening of depression and anxiety symptoms in this patient group.
We find that nearly all subcortical diffusion microstructure estimates at the baseline visit correlate with the depression score at the 2 years follow-up. The predictive nature of baseline free water estimates and depression subscores after 2 years are confirmed in the predictive structural equation modeling analysis with the thalamus showing the greatest effect size. We also find in the general linear model analysis patterns of MRI-free water differences in the thalamus and amygdala/hippocampus area between participants with high and low depression score.
Our findings suggest a relationship between higher levels of free-water in the subcortical structures in an early stage of Multiple Sclerosis and depression symptoms at a later stage of the disease.

Participants.
A total of 65 participants with relapsing-remitting MS as defined by the 2017 revision of the McDonald criteria 2 were recruited at the Department of Neurology, Haukeland University Hospital, based on written informed consent, approved by the Regional Ethics Committee of Western Norway (registration number 2016/31/REK Vest).
T 1 -weighted (T 1 w), T 2 -weighted (T 2 w), and T 2 -FLAIR MR imaging were part of a larger imaging protocol acquired in all participants, alongside with a neuropsychological examination of cognitive and emotional function at baseline as well as at two follow-up visits that were scheduled at approximately 1 and 2 years after the baseline examination, respectively. Diffusionweighted imaging (DWI) was performed as part of the MRI protocol at baseline and at the first follow-up, but not at the second follow-up.
Clinical examination and testing. For each visit, a separate clinical examination was scheduled close to the date of the MRI. The clinical examinations included the BICAMS examination comprising the oral part of the symbol digit modalities test (SDMT) 47 , the learning trials of both the second edition of the California Verbal Learning Test (CVLT-II) 48 and the Revised Brief Visuospatial Memory Test (BVMT-r) 49 . The BICAMS was developed to provide a short screening procedure for patients with MS 50,51 , and has been validated in a Norwegian study 43 .
EDSS was used to examine the disability status 3 together with the Fatigue Scale for Motor and Cognitive Functions (FSMC) 52 as well as the Hospital Anxiety and Depression Scale (HADS) 53 . The HADS is a 14-item questionnaire designed to assess the current state of the symptoms, with seven items each for assessment of symptoms related to depression and anxiety. The participant can respond to each question on a 4-point scale after which the points are summed up to give a score between 0 and 21 for each subscale. A total score is calculated as the sum of these two subscales 53 . The scores on the two subscales and the total score are included in the present study.
Image processing. T 2 FLAIR images were co-registered to the T 1 w images within the same imaging session using SPM12 (UCL, UK). Diffusion-weighted images were motion corrected, masked and eddy current corrected using FSL 6.0.1 (the University of Oxford, UK). FWF maps were created in native space using an inhouse routine. In line with previous publications, only b-values < 2000 s/mm 2 were used 18,19,54 . The resultant parametric maps from the diffusion imaging were subsequently also coregistered to the corresponding T 1 w image. MS brain lesions were outlined by icobrain ms (Icometrix, Belgium), an FDA-approved and CE-marked radiological services provider. Subcortical structures were segmented on the T 1 w images using the FSL FIRST tool after lesion filling had been performed. The segmented structures included separate measures for both left and right hemispheres of the following subcortical structures: thalamus, caudate, putamen, pallidum, amygdala, and accumbens. Measures over both hemispheres included whole white and gray matter, combined brain stem and fourth ventricle area and hippocampus. For analysis, the measures for left and right hemispheres of the subcortical structures were averaged. In the whole white and gray matter FWF analysis, areas with lesions were excluded by artificially extending each lesion with a 5 × 5 × 5 mm 3 Gauss filter and subtracting it from the analysis mask. For the whole white and gray matter volume analysis, lesions were filled-in before measures were computed.
As well as computing total volume and volume changes over time, segmented structures were used for masking regions of interest (ROI) in the free water maps.
To account for partial volume effects in these ROI masks when estimating free water, their size was reduced by applying the erosion function imerode in Matlab 9.5.0 (the MathWorks, Natick, MA). The strength of the erosion was set to be approximately 1/3 of total volume before erosion.
For the general linear model (GLM) analysis, individual T 1 w images were transformed into standard space based on the MNI152 T 1 w template. The transformation was then applied to the FWF maps from the first visit and images were subsequently smoothed with a 3 × 3 × 3 mm 3 Gaussian filter.
Statistical analysis. Statistical analysis was performed in Matlab 9.5.0 (the MathWorks, Natick, MA). Pearson correlations were computed between MRI data (total white and gray matter, subcortical structures volume, volume change between timepoints, FWF) and all test scores and responses on the questionnaires. Total number of test variables in the correlation matrix was 18 with 46 observations each. Resultant p-value matrices were corrected for multiple comparisons using false discovery rate (FDR) testing and only FDR-corrected p-values are reported 55,56 . A correlation coefficient greater than r = ±0.3 with a P-value < 0.05 (FDR-corrected) was considered significant.
To investigate whether FWF at the first visit can predict HADS and the other test and questionnaire scores at the most recent clinical assessment (the third visit), structural equation modeling (SEM) was set up using a partial least squares algorithm (PLS-SEM) 57 . For this, the 18 measurement variables belonging to the FWF mean values of each subcortical region and individual test and questionnaire scores were grouped into the following five latent constructs: FWF in subcortical region (including thalamus, caudate, putamen, pallidum, amygdala, and accumbens), EDSS, BICAMS (including SDMT, CVLT-II and BVMT-r), FSMC (including cognitive, motor and total fatigue scores) and HADS (including both the anxiety, depression and a total anxiety/ depression score). The model was set up as a formative measurement model.
For the GLM analysis focusing on symptoms of depression at the last clinical visit, subjects were grouped by their HADS depression subscore 0-2 (n = 23) and 2-9 (n = 23) as recorded at the 2-year follow-up and a two-sample t-test was performed to the FWF maps of the baseline visit in SPM12 (UCL, London, UK) with age as a covariate. The cut-off value of HADS depression subscore was chosen as it provided equal sample sizes.
Reporting summary. Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Results
Out of the 65 recruited subjects with relapsing-remitting MS, two opted out and withdrew their consent, two did not attend the baseline visit, four did not return after the baseline visit and seven did not attend for the 2-year follow-up. One subject missed the 1-year follow-up but had completed the baseline and 2-year follow-up visits, and was not removed from the dataset. A further three subjects had incomplete cognitive scores at the 2-year follow-up visit and were therefore excluded. In total, 46 participants had complete data collection at baseline and 2-year follow-up and were therefore included in this study, see Table 1 for participant demographics. MRI alongside with a neuropsychological examination of cognitive and emotional function at baseline as well as at two follow-up visits were scheduled at approximately 1 and 2 years after the baseline examination, respectively. The average time between MRI and neurocognitive assessment was 7.5 ± 31.0 days.
In the following, if not stated otherwise, all results are reported after multiple comparison testing corrections.
Mean values of FWF for each visit and ROI before and after ROI erosion are given in Supplementary Table 1. Testing for a relationship between depression and FWF in subcortical structures using PLS-SEM and GLM analysis. The PLS-SEM model converged in 301 iterations and fulfilled construct reliability of all latent variables with a Cronbach Alpha >0.7. Predictive nature of baseline diffusion measures and the HADS depression subscore was confirmed in the SEM analysis (total effect size of path: 0.46). Figure 1 shows the results of the two-sample t-test GLM analysis. Clusters of high t-values on this map highlight significantly different (P = 0.001, uncorrected) areas in the FWF maps between participants with low (<2, n = 23) vs. higher (>2, n = 23) HADS depression subscore. Clusters are clearly discernable in the amygdala, hippocampus, and thalamus. Additional clusters were also seen in the corpus callosum, cerebellar vermis, and precuneus.
Association of FWF in subcortical structures and anxiety subscore. FWF at baseline was correlated with the HADS anxiety subscore at the 2-year follow-up between the: Hippocampus (r = 0.35, P = 0.02) and amygdala (r = 0.38, P = 0.01).
In summary, FWF in all the segmented subcortical structures except for the caudate were correlated with one of the HADS metrics. FWF in the subcortical structures was also not correlated to any other clinical measurement at any timepoint.   Results from the volumetric analysis of the subcortical structures can be found in Supplementary Table 2 with atrophy measures in percent in Supplementary Tables 3 and 4. No statistically significant correlations between atrophy as a percentage-change and neuropsychological test scores were found.

Discussion
Changes in cognitive and motor function in MS are most generally recorded using a palette of different tests that aim to record different sets of performances. Such tests include the EDSS scale 3 , 9-hole peg test 58 , timed 25-foot walk, and/or more specialized tests focusing on the auditory and visual system 59,60 . In addition, quality of life, mood, and mental health 61,62 may be recorded with additional questionnaires that aim to register symptoms such as fatigue, pain, and depression.
Recommendations have been made on which assessment tools to include in monitoring of MS in standard practice and in clinical trials. The administration of these tools can, however, be time-consuming. Key targets of shortened exams, such as the BICAMS test 50,63 , are to cover a broad-enough range of cognitive domains to be sensitive enough to monitor cognitive decline and changes in relation to treatment. We believe there is benefit in adding questionnaires such as the HADS and FSMC. The HADS has been widely-used and by using well-defined score cut-offs for depression (above 8 out of a possible 21 a.u.), a meta-analysis of 747 publications found a sensitivity and specificity of HADS of approximately 0.80 according to the Cronbach alpha 64 .
We observed significant correlations between free-water in the subcortical structures and the HADS depression and anxiety scores. As a means to correct for partial volume, we used erosion to shrink the ROIs, thereby minimizing the effect of neighboring structures and tissues to our results. The FWF diffusion metric for a given ROI increased after erosion, implying that our findings are not related to increased diffusion due to partial volume with cerebrospinal fluid in the extracellular space that may have increased due to atrophy. If partial volume and atrophy were indeed a driver, we would have expected decreased FWF values after erosion. We therefore suggest that our observation is instead due to changes within the subcortical structures that could be driven by gray matter changes in those areas. It would be beneficial to investigate for the presence of subcortical gray matter lesions; however, identification of cortical and subcortical gray matter lesions in standard MR images is difficult 65 . It has been shown that cortical gray matter aberrations are present in the earliest stages of MS 66 and a post mortem study did confirm that both focal demyelinating lesions and diffuse neurodegeneration are common in the deep gray matter of MS patients 67 . The latter study also found that demyelination was most present in the hippocampus and caudate and could already be seen at an early disease stage 67 . An investigation into demyelination and lesions in the deep gray matter would be of future interest using specialized MRI sequences such as double inversion recovery imaging (DIR) that can aid gray matter lesion detection 65 .
We observed correlations between our free water diffusion metric and both the anxiety and depression subscores in nearly all subcortical structures. Hyperactivity of the hypothalamicpituitary-adrenal axis has been suggested to be an endocrine basis for the development of depression 26,68 and it is therefore not surprising to see the hippocampus and thalamus presenting with increased free-water, as seen in our study.
Only the caudate did not exhibit any correlation between the depression subscore and free water diffusion index. This is consistent with earlier research, suggesting that the caudate does not play a role in mood, depression or fatigue, but is rather associated with motor function and cognitive processes such as memory and learning [69][70][71] .
In our sample, HADS depression scores at baseline were 2.7 ± 3.0 out of possible 21 points and 5.0 ± 3.8 for anxiety, again out of possible 21 points and on the 2-year follow-up 2.7 ± 2.6 and 2.9 ± 2.7 for depression and anxiety, respectively. However, the theoretical upper maximum of 21 points is rarely scored, a cut-off of >7 is usually used to define a subject as suffering clinically from depression or anxiety 64 . Our sample therefore represents a good range between mild symptoms and what would qualify as clinical depression. Our results suggest that FWF may be a sensitive enough technique to detect depression early.
We employed false discovery rate testing as a means to correct for multiple comparisons. We chose this method as it has been previously employed 30 in this type of study and since Bonferroni-Holm or permutations tests were deemed unsuitable for this dataset: While the Bonferroni-Holm method penalizes a large number of comparison variables, permutation testing is more suitable for larger datasets such as those from genome sequencing 72 . To test whether baseline visit FWF could be used to predict HADS, we used a PLS-SEM analysis which overall confirmed the link between FWF and HADS. To move away from a ROI-based analysis we also employed whole-brain GLM voxelwise statistical testing that also highlighted statistically significant differences in only a few distinct regions with strong clusters in the amygdala, hippocampus, and thalamus, similar to our ROIbased correlation analysis results. This also highlights that not only are there differences in the subcortical structures that predict depression symptoms, but also that these are varied and their strength can clearly differentiate the cohort into two groups. The GLM analysis results did unfortunately not survive FDR correction, possibly due to the reduction in sample size by splitting our cohort into two sub-groups. Aside from the clusters seen in the amygdala, hippocampus, and thalamus, we also observed clusters in the corpus callosum, precuneus, and cerebellum. While we attribute the cluster in the corpus callosum and precuneus possibly to artefacts, the strength and distinctiveness of the cluster in the cerebellum is striking and requires further investigation.
All of the individual metrics of the BICAMS test battery correlated with the free water diffusion index in the cortical gray matter at the respective timepoints. A recent study by Genç et al. 73 that employed a diffusion-based neurite density metric in 498 participants demonstrated a strong association between cortical gray matter and performance on an IQ test. This may imply that diffusion in the cortical gray matter may also influence the performance in the tasks included in the BICAMS test battery.
In addition to the diffusion findings, we found a significant correlation between the results on the SDMT and hippocampus volumes at each of the respective timepoints and the r-BVMT to be correlated with the accumbens volume at both baseline and 1-year follow-up. The role of the hippocampus has been linked to memory, inhibition, and spatial cognition and has been related to cognitive changes in diseases like Huntington's and Alzheimer's disease 74 . Our findings may be explained by characteristics of the SDMT: In the SDMT task, the examinee is asked to match numbers with geometrical shapes during a period of 90 s, and by this putting a strong load on both memory function and spatial cognition. The r-BVMT is characterized by memory and learning components 49,59 . The correlation between r-BVMT and accumbens may therefore be attributed to the accumbens' contribution to learning, memory, and reward mechanisms, as was recently demonstrated in a model of dopaminergic neuron loss 75 .
A recent cross-sectional study by Fleischer et al. 30 demonstrated that subcortical volumes could be used as an early predictor of fatigue in MS. Fleischer et al. 30 found mainly that the caudate volume at baseline correlated with fatigue at a follow-up visit 4 years later. In our study, we saw correlations at the 2-year follow-up between cognitive fatigue and the thalamus, hippocampus, and amygdala. While we did not see a correlation between the caudate volume and fatigue, the highest correlation we observed was in the hippocampus (r = −0.43, P = 0.01), which the author of the Fleischer et al. 30 study suggested is involved mainly at the onset of MS. We therefore attribute the lack of caudate findings to the short disease duration in our cohort.
FWF is a diffusion microstructure parameter that can be computed in a few seconds from standard diffusion tensor imaging (DTI) acquisitions. Many centers include DTI acquisitions to facilitate fractional anisotropy (FA) and DTI tractography estimation, making all these studies potentially compatible with FWF estimation. More complex models that require longer, dedicated acquisitions such as restricted spectrum imaging (RSI) 76 or neurite orientation dispersion and density imaging (NODDI) 77 also include an isotropic diffusion estimate which should provide similar information to FWF. It may therefore be possible to reproduce our results with one of these models.
Our data may suggest that processes related to MS in the subcortical structures may contribute to the development of depression symptoms. If early changes in FWF can predict onset and severity of depression, clinical decisions can be taken to prepare the patients and their families with complimentary treatment for depression such as cognitive behavioral therapy.

Data availability
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to containing information that could compromise the privacy of research participants. Approval for data sharing is subject to approval by the author's local ethics committee and a formal data sharing agreement.

Code availability
The code used in the analysis has been made available online as Supplementary Data.